|
--- |
|
annotations_creators: |
|
- unknown |
|
language_creators: |
|
- unknown |
|
language: |
|
- en |
|
license: |
|
- mit |
|
multilinguality: |
|
- monolingual |
|
size_categories: |
|
- 100K<n<1M |
|
source_datasets: |
|
- unknown |
|
task_categories: |
|
- other |
|
task_ids: |
|
- natural-language-inference |
|
- semantic-similarity-scoring |
|
- text-scoring |
|
pretty_name: CORE Deduplication of Scholarly Documents |
|
tags: |
|
- deduplication |
|
--- |
|
|
|
# Dataset Card for CORE Deduplication |
|
|
|
## Dataset Description |
|
|
|
- **Homepage:** [https://core.ac.uk/about/research-outputs](https://core.ac.uk/about/research-outputs) |
|
- **Repository:** [https://core.ac.uk/datasets/core_2020-05-10_deduplication.zip](https://core.ac.uk/datasets/core_2020-05-10_deduplication.zip) |
|
- **Paper:** [Deduplication of Scholarly Documents using Locality Sensitive Hashing and Word Embeddings](http://oro.open.ac.uk/id/eprint/70519) |
|
- **Point of Contact:** [CORE Team](https://core.ac.uk/about#contact) |
|
- **Size of downloaded dataset files:** 204 MB |
|
|
|
### Dataset Summary |
|
|
|
CORE 2020 Deduplication dataset (https://core.ac.uk/documentation/dataset) contains 100K scholarly documents labeled as duplicates/non-duplicates. |
|
|
|
### Languages |
|
|
|
The dataset language is English (BCP-47 `en`) |
|
|
|
### Citation Information |
|
|
|
``` |
|
@inproceedings{dedup2020, |
|
title={Deduplication of Scholarly Documents using Locality Sensitive Hashing and Word Embeddings}, |
|
author={Gyawali, Bikash and Anastasiou, Lucas and Knoth, Petr}, |
|
booktitle = {Proceedings of 12th Language Resources and Evaluation Conference}, |
|
month = may, |
|
year = 2020, |
|
publisher = {France European Language Resources Association}, |
|
pages = {894-903} |
|
} |
|
``` |
|
|
